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Constrained electrical power systems and the long lead times ne eded for new capacity necessitate interim demand side management measures such as t ime-of-use (TOU) pricing. This form of electricity pricing has the potential to reduce system peak demand and thus improve the efficiency of power systems. Such time differenti ated pricing mechanisms have been used successfully in the industrial and commercial secto rs to shift demand out of the peak periods but have yet to be implemented in the residential sector in South Africa (SA). TOU schemes are based on the cost of supply and reflect, in part , the changes in short-run marginal costs. In contrast the conventional residential tariffs in SA are based on flat rate structures and recover long-run costs only. The analysis of the impact of such schemes, for both the utility as well as the customers, is gaining importance once more, particularly when most utilities are contemplating the implementation of smart s ystems and advanced metering infrastructures and the costs associated with this. A recent TOU pilot project, HomeFlex, is analysed from an ec onometric point of view. Panel data sets for both treatment groups and the control group ar e obtained from the pilot project database for each customer in two separate experiments in two separate geographic areas. The Caves and Christensen approach is used and the const ant elasticity of substitution functional form is chosen. Conditioning variables such as daily consumpti on per customer as well as climate effects are included in the ordinary lea st squares regression in order to establish the relationship between peak and off-peak consumption and the extent of the substitutability of these two commodities. The elasticity of substitution estimates obtained for stage 1 of the analysis range from 0.339 to 0.384. The conditioning variables enter the analysis as modifie rs to the estimates but their effect is insignificant. The stage 2 estimates range from 0.457 to 0.518. The effect of the conditioning variables is also statistically insignificant at this stage. The effect of the daily and weekly price ratio is therefore the primary factor in det ermining the response of customers to TOU pricing in the HomeFlex project. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2009.

by Yu-yee Wu. / Bibliography : leaves 113-120 / Thesis (M.Phil.)--Chinese University of Hong Kong, 1982

Marginal pricing is the traditional pricing method in pool based electricity markets, however pay-as-bid is an alternative that has been the focus of recent studies. One way of comparing the outcomes of these two pricing schemes is by examining their market equilibria. These equilibria have been analyzed in depth for both pricing methods under the assumption of a perfect market. Marginal pricing market equilibria has also been examined under oligopolistic markets, however, the same attention has not been given to oligopolies based on pay-as-bid pricing. / In this thesis, we study the possible outcomes of an oligopolistic electricity market under pay-as-bid pricing. For this purpose, we introduce, develop and test a new concept called defensive Nash equilibrium, which combines the risk adverseness of power suppliers with the traditional notion of Nash equilibrium. The test cases studied compare market outcomes between pay-as-bid and marginal pricing under various market power assumptions.

In an electricity market cleared by merit-order economic dispatch we identify necessary and sufficient conditions under which the market outcomes supported by pure strategy Nash equilibria (NE) exist when generating companies (Gencos) game through continuously variable incremental cost (IC) block offers. A Genco may own any number of units, each unit having multiple blocks with each block being offered at a constant IC. / Next, a mixed-integer linear programming (MILP) scheme devoid of approximations or iterations is developed to identify all possible NE. The MILP scheme is systematic and general but computationally demanding for large systems. Thus, an alternative significantly faster lambda-iterative approach that does not require the use of MILP was also developed. / Once all NE are found, one critical question is to identify the one whose corresponding gaming strategy may be considered by all Gencos as being the most rational. To answer this, this thesis proposes the use of a measure based on the potential profit gain and loss by each Genco for each NE. The most rational offer strategy for each Genco in terms of gaming or not gaming that best meets their risk/benefit expectations is the one corresponding to the NE with the largest gain to loss ratio. / The computation of all NE is tested on several systems of up to ninety generating units, each with four incremental cost blocks. These NE are then used to examine how market power is influenced by market parameters, specifically, the number of competing Gencos, their size and true ICs, as well as the level of demand and price cap.

Bibliography: leaves 350-383 / xx, 383 leaves : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--Dept. of Economics, University of Adelaide, 1984

M. Phil. / Presently, ESKOM is rated as the fifth largest utility in the world that generates and distributes electricity power to their consumers at the lowest price per kilowatt-hour (kW.h). As a utility, ESKOM is the largest supplier of electrical energy in South Africa and is currently generating and distributing on demand to approximately 3000 consumers. This represents 92% of the South African market. ESKOM was selected as the utility supplying electrical energy for the purpose of this study. ESKOM's objective is to provide the means and systems by which the consumer can be satisfied with electricity at the most cost-effective manner. In order to integrate the consumers into these objectives, ESKOM took a decision in 1994 to change the supply tariff from active power (kW) to apparent power (kVA) for a number of reasons: To establish a structure whereby the utility and the consumer can control the utilisation of electrical power supply to the consumer. To utilise demand and control through power factor correction and implementation of load management systems. To identify some cost implications of electrical power factor correction and load management. Consumers with kW maximum demand tariff options had little or no financial incentives to improve their low power factor (PF) by reducing their reactive current supply. Switching to (kVA) maximum demand will involve steps to be taken to ensure that the reactive component is kept to a minimum with maximum power factor. ESKOM has structured various tariff rates and charges with unique features that would accommodate the consumers in their demand side management and load cost requirements, which, when applied, will result in an efficient and cost effective load profile. These tariffs are designed to guide consumers automatically into an efficient way of using electrical power, as it is designed to recover both the capital investment and the operating cost within two to three years after installation of power factor correction equipment. ESKOM's concept of Time-of-use (TOU) periods for peak, standard and off-peak times during week, Saturday and Sunday periods is discussed as load management. Interruptible loads can be scheduled or shed to suit lower tariff rates and to avoid maximum demand charge. The concept of load management will change the operation pattern of the consumer's electricity demand whereby the consumer will have immediate technical and financial benefits. In the last chapter of this dissertation, a hypothetical case study addresses and concludes on some of the technical and cost implications of electrical power factor correction and load management as a successful and profitable solution to optimize electrical power supply to the consumer. By implementing the above, ESKOM ensures that the consumer utilizes the electrical power supply to its optimum level at the lowest cost per kilowatthour (kW.h) generated.

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